How I am Investing in Lending Club and Prosper in 2012

One of the things I love about p2p lending is the transparency. By this I mean that anyone can download the entire loan history of Lending Club and Prosper and analyze the data for themselves. I am trying to bring a level of transparency to my own operations on this blog by giving you an inside look at my investments.

Last month I provided a snapshot of all my p2p lending accounts and today I will continue along on that journey by revealing exactly how I am investing in Lending Club and Prosper today. I first detailed my investment criteria nine months ago in a post that described how I was investing with Lending Club and Prosper back then. I gave you two strategies each for both companies and today I am going to expand on that.

No More Conservative Lending Strategies

The biggest change in my investing in the last nine months is that I have ditched the conservative lending strategy at Lending Club. In my main Lending Club account I had been focusing on B- and C-grade loans for quite some time. But I decided that was simply leaving money on the table so late last year I switched course and decided to focus purely on loans grades of D and below at Lending Club on all my accounts (except for my Lending Club PRIME account).

Now, this created something of challenge. As I detailed in my last post I want to invest in multiple p2p lending accounts without investing in the same note twice. So, after spending way too much time on Lendstats exploring hundreds of combinations of selection criteria I came up with these sets of filters that provide no duplication of notes. I have provided a link below each filter to the Lendstats page that shows the returns one might expect when running these filters. If you don’t know what some of these fields mean you should learn more about credit reports (just google “understand credit report” and you will find plenty of articles).

You can see that the main difference between Filter 1 and Filter 2 is the stated monthly income. I use that field to ensure that there is no overlap between loans when I am investing in multiple accounts. You will also notice that both filter 1 and filter 2 use inquiries = 0 as a criteria so this opens up the door to use Inquiries of one or more for Filter 3. Because all three filters don’t invest in loans originated in California I could easily setup a fourth unique filter for loans just issued in that state. I haven’t done this mainly because there are not enough loans that meet my criteria.

One point I should make is that if you use the Lending Club website to invest then you will not be able to use these filters as is. The filtering capabilities on their website are not flexible enough to allow for this kind of precision and some fields such as monthly income are not even available. So what I do is download the spreadsheet of all available loans from the Browse Notes page – there is a small Download All link in the bottom right of the screen. Then I can do the filtering in Excel and invest from there.

The bulk of my new investments on Prosper go towards repeat borrowers. I have found repeat borrowers to be an excellent group of borrowers and you can see by clicking on the Lendstats link with each filter that they provide excellent returns.

Long time readers will know my love of the Number of Inquiries filter so you might be surprised by Filter 2 where I go with number of inquiries between 2 and 5 (I have long maintained that inquiries = 0 is one the best filters you can have). But I let the Lendstats ROI numbers be my guide here. And even though a previous borrower has two or more inquiries on their credit report with the additional filters in place here you can still generate an excellent ROI.

Now, I don’t want to be one dimensional and ignore new borrowers, so filters 3 and 4 provide a way to invest in new borrowers that is also likely to produce a good return. Again I am using number of inquiries as the way to separate the note selections to avoid duplication.

So, there you have it. These are the criteria I am using to invest today. It makes investing with multiple accounts a breeze or you can just as easily use these criteria on one account. Feel free to use these filters yourself if you like. Or you can always critique them and provide your own suggestions in the comments.

Related

Comments

Again, on behalf of my fellow Californians, I must protest on our seemingly blanket exclusion from consideration. We are a great state with incredibly responsible people. You can always rest easy with the knowledge that your investment is completely safe with us. No Californian would ever consider walking away from a debt except as a second or third resort. 🙂

Very interesting loan filters for LC, particularly that you are focusing on lower grade loans now. Have you determined that the higher interest rates those notes pay more than offsets the increase in defaults you experience?

I’ve also been a B and C note investor (and a few A and D here and there). My biggest concern about investing in notes that are charging 20%+ interest (E, F, G) is that these borrowers are less likely to be doing it for debt payoffs, vs things like home repairs, medical or wedding expenses, small business startups, etc… where I think they are riskier uses of the funds.

As myself & others have stated here 127 times previously, the truth is that we really have no idea what the borrower ultimately does with the borrowed money. Personally, I assume that regardless of what they “say”, they will in fact spend it, rather than pay off debt. It frankly makes no difference to me as I’m not here on some misguided social do-gooder mission. I’m just here to get a high return.

I’m no longer a Prosper investor (for totally unrelated reasons) but in a sort of perverse way, those who are HEAVILY concentrating on “repeat” Prosper borrowers (like Peter) also recognize that the ultimate best borrower is one who will keep “repeat” borrowing & remain perpetually in debt while making his high interest monthly payments on time. I have no problem with that reality either. Just being honest about the dynamics & reality of the situation.

@Dan, I would like to include some CA borrowers in my Lending Club investments but I simply cannot make the numbers work with a large enough pool of loans. As more history build up that may change but you can take solace in the fact that I do not discriminate against CA on Prosper.

And yes, I do realize that repeat borrowers on Prosper paying 20%+ are rarely going to be paying down debt. I have somewhat struggled with this philosophically but I have decided that these people are still benefiting from being able to access money even at these high rates. If they were not borrowing here they would probably be racking up more credit card debt or even going the pay day loan route. A fully amortized fixed term 24% loan is a better deal for them in most cases.

@Danny, Yes, I have determined that the lower grade loans provide the best chance at a high return. And that is my focus. I don’t mind getting some defaults on 20% loans if, at the end of the day they produce a 12% return. Getting that kind of return by investing in B and C-rated loans is extremely difficult.

@Charlie, I am fully aware that stated income is mostly not verified. I am not relying on verification for my decision. Nor am I concerned about loan purpose. I let the loan history data be my guide. For my Lending Club Filter 1 I know that many of these people may not be earning more than $7,500 but the loan history provides return information on those people who say they earn that much. That is good enough for me.

Peter I find some of your insights to be quite fascinating. I dont know if I can get my head aligned with G graded notes, but I am going to take a closer look a D, E, F notes.

My big concerns for those notes are monthly income (even if not verified) vs monthly payment… I try to keep to a ratio of no more than 15% of a person’s income going towards their LC loan. That has seemingly worked quite well in keeping defaults low for me.

I also dont like having borrowers which show any delinquencies within the last 4 years, so that also affects the # of loans in the pool available to me. But will see how many of these lower grade loans are available in my comfort zone.

I see many people create filter strategies that attempt to get a handle on risk. But I have seen few people use risk in combination with reward to choose their loans. This is my approach. I predict a charge-off probability for each loan in the database (based on historical predictors), and then compare it to the interest rate to calculate an expected value for the loan. I rank by expected value, and choose the top loans in which to invest.

The mutually exclusive filters is a poor idea in my opinion because it creates an artificial partition on the data. You could literally be choosing “the cream of the crap!” It makes much more sense to look at all loans simultaneously and choose the best ones.

Those who don’t pay attention to stated use are leaving valuable information on the table. Stated reason is a statistically meaningful predictor of charge-off. It doesn’t matter whether people use it for the intended purpose; on average it is a valid signal.

@Danny S, It does take a bit of a leap of faith to take a look at the higher risk loans. I was investing for over a year before I even considered a higher risk loan. Now, they are my complete focus because, if done well, they provide the best chance for a high return.

@Larry V, You are welcome.

@Bryce, What you describe is an interesting concept and reminds me a bit about what SmartPeerLending.com is doing. The way I look at it is that Lendstats in essence provides the same thing. Because they take into account defaults and late notes you are getting a window into a charge-off probability.

Looking at all loans simultaneously is the best solution for most people who have just one account. But if you have multiple accounts you need an investing strategy that partitions the loans unless you want to duplicate your portfolio across different accounts.

Thanks a lot for sharing all this valuable info. I’d like to touch on a few topics:

What’s the reasoning behind DTI% = 8 ? Did you just trial and error on lendtats until you found the magic numbers?

And what about avoiding CA? Did you try excluding each state at a time until you found the worst offender? Any idea why?

I’m very surprised to see you allow 2+ inquiries applicants. I understand your desire to come up with different criteria because of your multiple accounts. I’m not sure giving up on what has been a great predictor makes sense for those of us with a single account.

Finally, I’m surprised you don’t filter more selectively on loan purpose. It seems to be an pretty good predictor also. Do you disagree?

Partitioning the loans will never yield a profit maximizing solution if you insist on nonzero investments in all portfolios. I think I could prove it, but it seems intuitive to me anyway. Maybe at best it will match the profit maximizing allocation, but seems unlikely.

If one filter is superior to another, then you would always be better off by investing more in that space with the money from the weaker filters portfolio. My 2cp.

How about the P2P companies start offering balance transfers, having the the borrowed money go directly to the credit card companies owed. This would be noted on the note listing, and I’m sure these notes would get funded much quicker. Now let’s see who will jump on this first…

My two cents for what it’s worth:
1) Risk as a measure to whether one should choose A-G rated notes should be compared against one’s entire portfolio, which hopefully does not include just lending club or prosper products. A healthy balance of other assets (bonds, stocks, CDs, ETFs, Real Estate, whatever) will by its very nature permit you to entertain higher risk (E-G) notes if you are wanting to dabble with that asset class. I happen to agree with Peter and the other comments above that it is a class worth taking seriously. Consequently, if you find yourself curious or interested in the E-F notes, simply offset it with something else (outside of member dependent notes altogether) and you should be fine to at least experiment.
2) Speaking of diversification, I have often wondered if a P2P company will one day provide us with a platform where we can invest in credit card debt directly (funding the actual credit card’s “credit”) instead of investing indirectly in credit card debt as we do now (by providing the credit for prior credit card debt consolidation). Considering how large a market credit card use has become, one could only wonder the investment potential awaiting the first P2P platform that could service those instruments directly.

Thanks for your ideas. I still don’t understand the rationale for excluding certain states?? And how did you choose which to eliminate?

Also the criteria you list don’t fit the filters on Lending Club. For instance you use 23% DTI in your first example and Lending Club allows selection only in 5% increments. Also you want a minimum stated income and there is no such criteria on LC? Or do you use lendstats to find the loans then link back to lending club to purchase them?

@Frankie, I have spent dozens of hours running several hundred queries on Lendstats and I have let the results from this process be my guide. Keep in mind that you need a decent pool of loans to have any query be statistically significant – I always like to see each query generate at least 500 loans before I consider it a good predictor of future results. Then I will re-run the query over several months to see if it continues to provide a consistent ROI. You are right that loan purpose can be a decent predictor of return and I know many people who use that as an important basis for investing decisions. There are plenty of other ways to generate good returns – these are just the ones that I have chosen.

@Bryce, If it was absolute that a certain criteria would produce the best results then I would agree with you that it would always be better to just invest in the best loans. But the fact is we are working with a moving target. The loans that you have isolated as the best loans may end up proving to not be the best when all loans have reached maturity. We need a loan database many times larger than what we have and underwriting standards that don’t change before we can be completely confident in our choices. This is another reason to choose different criteria – some of them will continue to perform well while others will likely underperform expectations.

@Moe, That is an interesting idea and I can see something like this becoming a reality in the not too distant future.

@Chris, Very good point about considering p2p lending’s role in an overall portfolio. That is really a key point that all investors should take into account. For most investors I think it pays to be more aggressive with their p2p lending holdings, because most people hold a mix stocks, bonds and cash. For the reasons you point out this should make investors feel more comfortable with higher risk notes. In reality, though, most people treat p2p lending in isolation and focus on the higher grade notes.

I think one day, probably several years from now, Lending Club and Prosper will get a banking license and issue credit cards directly. Then finally we can get the traditional banks out of the equation. But they would need to be several orders of magnitude bigger before considering such a move.

@James, You have pointed out the main reason I do not invest with the Lending Club platform. I download the in-funding notes to an Excel file and do the filtering there before going back and investing in the loans on Lending Club. On Prosper this isn’t necessary because they have much more flexible investing criteria.

As for the states, I only consider the largest states for exclusion. Even though states like South Dakota has performed poorly at Lending Club I don’t bother excluding them because so few loans are issued there.

I don’t think your argument that you want multiple criteria is solid, Peter. For example, if what you say is true then you wouldn’t be neglecting CA loans because things might have changed since the loans used to make that negative relationship finished. You would be using CA loans because they might be stellar performers in the future. But, you do not, presumably because you also hold the belief that about all you can do is use the past to predict the future.

. The best we can do is to choose criteria that have a string theoretical basis and empirical evidence and hope they continue to perform in the future.

@Bryce, I agree that is the best we can do and if I had just one account then I would be doing exactly what you suggest. There are literally millions of combinations of loan filters that we could use and I am choosing just a handful of the top one that have performed well historically.

As for your point on CA loans I would be open to a filter based on those loans because the vast majority of them have performed well. If we can isolate those loans then we would have a successful strategy.

Anyway, we might need to just agree to disagree on this one. I take your points but I will continue on with my strategy.

I’m curious if you and others are doing any manual filtering based off answers and written descriptions. I use similar filters as above and then base my final decision off seeing some written answers. If someone wants a loan for $35k and they can’t be bothered to write anything anything beyond, “creidt consold” then I skip it. However, this can really limit the number of loans available for me to invest in since a fair amount of borrowers don’t write anything. I am curious if I’m biased against these loans for no good reason and what others take on it is.

I remember reading articles a while back that showed a positive correlation between word count and ROI, but that was a while back and I really haven’t seen too much discussion about it since.

I’m the same way. I have a variety of filters, but I read every loan description I’m considering. I definitely run away if they are asked specifics and answer with generalities. I’ve also noticed that many of my defaults literally contained some “desperate” language that I used to ignore. On a side note, in case LC is watching, it would be great if I could look at a loan, then hide it or mark it somehow so i don’t keep reading the description.

“I remember reading articles a while back that showed a positive correlation between word count and ROI, but that was a while back and I really haven’t seen too much discussion about it since.”

Would you happen to remember where you read this material/article? I would love to look at that data as I have often wondered the same thing with regard to possible correlation between description and default rates.

There is also another post somewhere that also has a list with the 10 worst and 10 best words in the description section. I think the ten worst mainly included familial relationships, like child and children. I think another of the worst was “help.” That article might take me a little more time to find.

On the topic of descriptions, I wonder if there is a correlation between the quality of the spelling (@Chris’ “creidt consold”) and the default rate. It would be interesting to massively feed descriptions into a spell checker, come up with a metric (errors/100 words?) and then correlate that to default rate over time. Or am I taking this too far? 😉

@Frankie, Hmmm. I am thinking that would be a very difficult one to implement because people might use prosper nouns or abbreviations that would be picked up as misspellings. It bothers me, too, when people can’t spell but automating that as a filter would be very challenging I would think.

@Bryce. No worries – I have copied your comment from there. Here is what Bryce is talking about:

People were interested in loan description length vs. charge-off. I figured since loan descriptions aren’t going to come back, I’m happy to share a couple graphics. Although it looks like there’s a bowed relationship, it’s statistically borderline (~p=0.09) because the vast majority of the data is between 3 and 7, where it’s essentially the flatish part of the charge-off curve. There’s not enough data to suggest the tips of the curve are really that bowed (as noted by the 95% confidence interval).

Just a followup, people should look at both graphics. The first is a histogram of the distribution of the lengths. The second is the money graphic, showing the relationship to charge-off. I note this because the second graphic only had 1 view where the first had 10. People may have thought that the link was just one continuous thing.

Loans with the word “bills” in the description were 6% more likely to charge off. “Bills” was in the top 50 words used.

Loans with “bible,” “God,” or “pray” defaulted at a 35% rate compared to a population 22% charge off rate, but the result was only borderline significant because there were just 25 such loans among the first 3200 in LC’s history.

@Bryce Very interesting, thanks for passing those graphs along. Just curious, on your loan description axis it goes from 0-8 characters, but have you looked at beyond 8 characters?

The lendingclubmodeling link and lendingtuber where the two articles I remember reading. However, I thought lendingtuber’s findings (on Prosper, not Lending Club) that the shorter the description the greater chance of getting paid was surprising and looking for other research to back that up.

@Bryce, I am a huge fan of studying historical loan data but I am still unconvinced about analyzing keywords. Before I draw any conclusions here I would like to see if the trends remain the same with time and I am not sure we have a big enough loan pool yet to see that.

I wouldn’t waste everyone’s time reporting statistically insignificant results. These are the patterns over all of LCs completed loan history. Some words may not have enough appearances to say much, and that’s why I looked at the top 50 commonly used words only (and many of those were boring and not bother to check like articles the and a).

I suppose one way to validate it would be to predict delinquency on the currently in repayment loans population. I have been thinking of making more use of that data to see if my modeling holds on more current data anyway.

@Bryce, That is precisely the kind of thing that I am interested in. If we can predict delinquency on current loans and if these predictions remain true going forward then we will really have a useful model.

The problem is that defaulting is not the same outcome as charging off. I have done all my modeling with chargeoff or paid in full as the outcomes. Obviously many loans that default wind up curing themselves, so things that predict default may or may not be the same or of the same strength as for chargeoff.

I do two things to test my model. First When I built my model I put a portion of the data aside and then tested the model’s performance on it. Once since I’ve completed it, I tested the model on all the loans that completed since the last loan used on the original model. That is, as time passes, more loans complete to study. But the problem is that they are always three years behind the loans to fund today.

The hope is to build a set of leading indicators to keep an eye out and ensure that the predictors are continuing to perform as expected.

@Bryce, Thanks for the fuller explanation – I can certainly see you have done your homework. But you do bring up another relevant point: we are working with a moving target. Lending Club has changed their credit policy dramatically from 3 years ago and some loans issued back them would not make it on to the platform. I presume you are excluding those loans from your analysis.

We can’t get a perfect model because Lending Club is always tweaking their risk and underwriting models, but we can still get something that is close.

I would like to share more details about your work with the readers here if and when you are willing.

I definitely knew that LC tweaked their eligibility criteria, and when I built the model I used a technique with an indicator random variable on that set of loans to see if, after all of the other variable I was using, there was still any basic difference for those loans. After all of the work that I did, I no longer had to treat them any differently. It was clear that LC selected better borrowers on criteria that they were disclosing to lenders. So, in the end, we can use those loans to model with also.

I’d be happy to have a conversation with you any time, Peter. You have my email.

Bryce…………I’m sorry, but defaults & charge offs are in fact virtually the same thing. Almost no loans that default “cure themselves:” as you put it. I have no idea how you could come to that conclusion.

Perhaps it is a definition difference, but many people do miss a payment deadline and subsequently fix their situation. The outcomes for loans in repayment are essentially four: (1) paid in full, (2) late of varying degrees, (3) charged off, and (4) current. I am equating “late” to default.

I do not like the word “default” because I have not seen LC define it precisely. It is a meaningless marketing term to me that I cannot associate to any of their public data. I’m sorry if I’m just ignorant of a commonly accepted definition.

The main point is that it is hard to analyze loans in repayment in a way that is meaningful and to get a set of leading indicators because we simply don’t know how the outcome of “late” is going to shake out. LC doesn’t give us the whole payment history so we can model that. That’s why I just simply skipped the middle steps and modeled the end state of charge off vs. full payment. That’s what matters in the end anyway.

As further proof that “default” and “charge-off” cannot be the same, LC consistently states its default rate is something like 3%. The facts are that the charge-off rate for all loans that have completed is around 22%. These are so different as to be comical to assert they mean the same thing.

I tried to reproduce this number many ways, but about all I could come up with was that it is the instantaneous proportion of late loans. That is, at any given time, there are about 3% of loans that are delinquent. These risks accrue over time, some cure, some charge off, and we wind up with about a 22% charge-off rate.

As a mathematician, it is extremely frustrating (but not at all surprising) to see people throw around words without precise definitions. One of the first things I did with the public data file was to try and reproduce LC’s numbers, such as the 3% “default” rate. I assumed that they meant only 3% of their loans went bad. Imagine my shock when I looked at the loans that had run their 3-year course and found almost 23% had charged off.

A 3% instantaneous delinquency rate sounds much more appealing than 1 in 4 of our loans charges off. I can see why they went that route. But of course all investors do plenty of due diligence to know this, right? =)

Who apart from you is suggesting that the 3% figure is a static number since inception?. A bit over 3% per annum CURRENTLY is what I said. Historically it has been higher than that figure. So I don’t see a massive problem with the arithmetic. And I used my fingers & toes to help me add 🙂

I suppose that could be possible, but it will require that the ultimate chargeoff rate be in the 9% range for 36 mo term loans. That would be quite the improvement and I do not expect that level of improvement based on their stricter criteria. But hey, could be! And my returns would be very appreciative. The main point is that there shouldn’t be this level of ambiguity, especially on a board devoted to the topic!

LOL that is enough to show it’s a quirky marketingese term, and I would still like to see how they are defining it carefully. In some ways I don’t care though, because I just model charge off and that’s the thing one should strive to avoid.

Don’t get me wrong. I think the charge off numbers will end up higher as well. I’m not 100% sure but I think the charge off numbers for the first 3 full years was north of 16%. Also keep in mind that about half of LC loans are now 5 year loans which may or may not have the same payment patterns as the 3 yr. ones.

Interesting discussion gentlemen. Let me throw a curve ball at you. I have seen this 3% default rate being thrown around now for over a year. And it is simple to justify.

I don’t know exactly what Lending Club mean when they say a 3% default rate but it could mean that 3% of the unpaid principal (we are not talking about number of loans) is written off each year. This to me is more likely to be the number, and frankly it is more meaningful than number of loans. Because, as I have stated many times, a default in month 24 is very different from a default in month 2.

@Chris, I will work on getting an official definition of “default” from Lending Club. It seems to me that loans stay in this mode for a couple of weeks or more before charging off. Prosper only has one category for these kinds of loans.

I’ve been hearing that 3% number for years as well………..but I’ve never believed it.

On the subject of late loans, defaults etc., when you get a chance, please ask Lending Club what percentage of their 5 year loans are currently on some type of “payment plan”. The answer to that question is just a curiosity today, but I guarantee you that in a couple of years the importance of that question & answer will become apparent…………& Lending Club investors are not going to be amused.

@Dan, I wrote that last comment in a hurry as I was on a train and about to go into a tunnel and lose my internet connection.

Anyway, what I am saying is that I am sure Lending Club can justify the 3% number backed up by solid data. I have been keeping track of the data in the Loan Details page in Lending Club’s statistics area for about eight months now. Exactly six months ago Lending Club’s total loan portfolio stood at around $338 million. In the last six months there have been $5.45 million in defaults – an annual rate of $10.9 million. When you divide that number into the total loans outstanding from six months ago you get 3.2%. Bingo, a 3% annual default rate.

I am not saying this number has much relevance because such a large percentage of the loan portfolio on LC is always so new, I am just saying this is one way you can get to the 3% annual default rate number.

As for your five year note question it seems to me that LC are very quick to put borrowers on a payment plan and once on that plan borrowers tend to just stay on it or default. I agree, though, I think investors should pay close attention to those five year loans – they are still an unknown animal at this young stage.

Hi Peter,
I’m new to the P2P lending model, late to the game. I’m doing research on it mostly out of curiosity. I do get the feeling that some version or another will ultimately be successful. Lending money is not rocket science and banks have a very poor rep among the masses. It may be ignorant and jealous and myopic but many believe banks are evil. It goes in cycles and has been strong lately.

Still, some of the impressions of savvy investors I’ve read about P2P are quite damning. I think that removing the Q&A is problematic. Can we really automate a large-scale system of this thing? Are poor credit scores and hounding collection agencies really enough to keep borrowers from defaulting? The old way, the bank way, put at least a little personal pressure on the borrower: “Jim, I’m funding you because I believe in you. Even though you have nothing. Don’t let me down.”
An algorithm can’t do that.

@Manny, Yes I believe we can automate p2p lending. Banks for had automated underwriting on credit cards for decades and it is one of the most profitable areas of their business. Lending Club and Prosper are merely applying that model to p2p lending. As for poor credit scores and agencies being enough to keep borrowers from defaulting? It seems to be so far. Remember that most people are honest and the vast majority of scam artists don’t make it through underwriting.

@Simon, Everything I do is based on the results that I see on Lendstats. For my first LC filter allowing delinquencies actually improves the ROI – it is counterintuitive I know but I let the numbers guide my decisions.

The one thing about the A, B and C loans is that on the whole these are more creditworthy borrowers. If we end up having another bad recession I expect that these borrowers will hold up better than those with grades D and below. But I am willing to take that chance.

It’s been a few months since you moved to the more agressive lending approach with LC. Have the results been favorable? I just jumped in to p2p yesterday. I funded a Roth IRA with $5k. I want to see what I can do with this small amount before I add any more funds. I need a return of 10%+ (and I know it might take me a while to reach that goal). I am no stranger to risk as I have been fully invested in the stock market over the past 20+ years. That didn’t always turn out positively so I am willing to give this a real chance. I just wanted to check in with you after it’s been a few months with the new approach.

@Tim, Well congrats on your recent move into p2p lending, I think you will be very pleased with the results. Since moving to my new more aggressive strategy I couldn’t be happier. On new money invested with this strategy which I started about nine months ago I am averaging a bit over 14% real world return (i.e. not what Lending Club tells you). Now, as these loans age I know I will get more defaults but I expect returns to level off in the 11-12% range. So, I think your goal of at least 10% a year is doable. Best of luck.

Peter, Just an update:
Thought you might be interested in my results so far since I have tried to attach myself to your coat tail. My NAR is 12.93. I had (2) notes pay off early–I thought that was a little unusual. And out of 208 loans, only 1 is in the grace period. I am eager to see what happens over the next few months. But, so far–after 2 months, I am very well pleased with my p2p experience.

Simon, I have reduced my exposure to 60-months notes slightly in recent months. I was putting about 50% of new money into 60-month notes and I have dropped that to 25-30% now. With the recent (around January) change in Lending Club’s underwriting I think 60-month loans will actually start performing better but I think it is still prudent to be cautious.

Peter, I notice that your filters do not include the requirement of verified income. Is that something that you are not really concerned about? I have tried to avoid notes where income was no verified. Am I making too much of that?

Tim, You are correct in seeing that I do not take verified income into consideration. The reason is that I read an article a while ago where Renaud Laplanche stated that loans with unverified income slightly outperform loans with verified income. Now there are reasons for this, one of which is that more creditworthy borrowers are less likely to have their income verified. I would really like Lending club to include the verified income flag in their data download but until they do I am not going to be including this as a filter.

i recently came into a substantial amount of money and really want to help people in need. i never have invested like this before so please tell me in simple language — about how many of these loans default and is there a method for collections on defaults?also, someone told me to look at loans that are more than 50% already funded to invest in….is there any logic to which loans to invest in or is it all just hit or miss? considering investing upwards of $500k or should i start smaller to get my feet wet?

John, I wish I could give you a definitive number on default rates but the answer is it depends on what kind of loans you invest in. If you are focused on the low risk borrowers (grade AA and A) you can expect an annual default rate of around 1%. If you go for high risk borrowers (grade E and below) you can expect an annual default rate close to 5%.

The reason people invest in loans that are at least 50% funded is these are the loans that will be more likely to originate. So you will not be tying up your money as long in these kinds of loans. But there is no evidence that I have seen that these loans perform better over the long term.

Finally, if you are new to p2p lending I recommend you getting my ebook – just put your email address in the box at the top of this page. If you are interested in learning I think you can do better than the average. But with that amount of money to invest you have a lot of options. Feel free to email me through the contact page and I can put you in touch with the relevant people at Lending club and Prosper.

Hey John, I actually am looking for a substantial loan if you still have your $. I have two properties in Santa Barbara, CA that I need to refi but can’t because my loan to value does not match what the banks want due to the market crash. I am not really underwater though, I just don’t have enough equity yet but with the market improving and working a lot of overtime I hope to get there before rates go up. A little about me…. I am a 13+ year firefighter for the City of Santa Barbara with a credit score of 815. Never been late on anything, ever. I have no debt except for my house loans. Ideally, I would be able to get a personal loan for about 50K and give that right to the bank. This would be enough for me to refinance my current adjustable loans into fixed loans and then I would just owe you. I would be willing to sign any contract you would like, verify my income, anything. I don’t know what your risk tolerance is or what you are looking for in returns but I really am a sure bet. Thanks for your consideration, J

Hi Peter, I’ve been a real estate investor for over 45 years, retired from J.O.B. at 42. Been looking for other ways of investing for many years, but NOTHING comes close to what I get in returns from my reat estate investments. Just found your site today and like it, you sound open and honest, traits I really like. Going to read a lot more here to learn as much as possible. If one can get 10% or more return, NO customers or renters and the freedom to sell at anytime, NOW that’s my kind of investing! If the market picks up and can sell for a reasonable price, I WILL be contacting you to learn your methods. Keep writing and the best of returns to you.

If you read my latest post on my annual returns you will see that I have made 9.57% in the 12 months ending 6/30/12. That number should go over 10% by the end of September. So, yes 10% returns are indeed possible. And while you do have the freedom to sell at any time if you did need to liquidate your entire portfolio you may lose 3-5% in the process.

I’d give a warning to any new investors considering putting money into Lending Club. Lately, they’ve been sending out notices to many of the people who have borrowed. Here’s how that works:

1. Borrower requests loan. Investor assumes they will get interest over the life of the loan and pay a 1% fee to Lending Club as the loan is paid back.
2. Borrower’s credit score improves when they use loan to pay down credit cards. Seeing this, Lending Club contacts the borrower and encourages them to take out a new Lending Club loan at a lower rate (because of their improved credit score).
3. Borrower does this and pays back first loan in lump sum. Investors get shafted, as they pay the entire 1% fee on the principle without getting the interest on the full life of the loan.
4. Investor must now take the lump sum and find another loan to try and invest in.

In short, investors pay far more than a “1% fee” in practice, and Lending Club does little to respect their investors.

This high turnover also makes it frustrating investing at Lending Club. It takes a lot of work to find good notes to invest in, and then Lending Club encourages the borrowers to re-fi and take out new loans to pay off their first.

I hear what you are saying but I wouldn’t characterize this as “investors get shafted”. The loss to investors in a prepayment is a very small percentage which has little impact on the investors overall returns. It does mean there is a lumpsum to reinvest, however. If you choose loans manually then I can see how that would be annoying.

But keep in mind this – good borrowers have choices and Lending Club (and Prosper as well) have to keep this in consideration when marketing to borrowers. The lack of a prepayment penalty is certainly a nice benefit for borrowers and from my opinion as an investor that is something I can live with. It is one less loan that could possibly default.

I am currently trying to implement your filters on prosper however I find it a bit difficult to take your verbage and apply it to the “Additional Criteria” that prosper allows us to utalized. Is there a way you can use a screen shot ect… for example I am setting up an automated plan and the you state payments on previous loan it states 12 but on their criteria it has on time payments billed % to % of total payments billed. It also has credit score any to any but you put down drop up to 100 from what number are we starting…. I see the following:

Additional Criteria

Credit score Any to Any

Now delinquent: to delinquent accounts

Inquiries in last 6m: to inquiries

On-time payments billed: % to % of total payments billed

<31 days late payments billed: % to % of total payments billed

I am just having a hard time following how to apply the filters you are speaking of… is there a youtube video or screen shot somewhere.

The number of late payments is the <31 days late field. There is a Credit score change field that I use and the Total payment billed. Make sure your Search Criteria matches the graphic above and you should be good.

I know that it is a slightly older post, but this is very useful to be able to see the way you have built your filters based upon what you have learned from LendStats and experience in investing over the years. I’m sure that your investing strategies will continue to evolve, but after the recent demise of LendStats, do you have any thoughts about how you will statistically continue to inform your investment decisions, specifically regarding Prosper investments? As an incoming p2p investor, I’m sad to see that I’ve missed such an important tool.

Jim, It was sad to see Lendstats shut down for Prosper investors but the good news is that there are more options now. You should check out a new site that I think is even better than Lendstats – I wrote a review including a video last month:http://www.lendacademy.com/prosper-stats-launches/

Peter thanks for the information….. I just set up your first parameters in my Prosper account. I see that you run 3 papameters… do you run one of them one month, then another one on the next month and so on… because it asks for priority or do you just run them all with no priority?….. I have dabled with Prosper since i2008 but really at that time just threw some money at it to see what would happen…. my returns where less than stellar but each year I did better..

2008: -4.78%
2009: 3.32%
2010: 4.67%
2011: 8.65%
2012: 7.65%

So as I am getting better overall I am looking to get in the 9-10% club. I have very little invested at this time just but have more funds I could put this way. Do you suggest opening a lending club account also to “diversify these investments”. Or should I wait until I have a 5 figure sum in prosper before doing somthing like that. I have read your ebook and in interested in your prospective in these matters.

Oh sorry I should let you know that I currently have 280 active notes and at this time I am investing approx .5% of my total balance on each note as this spreads the loans over a wider aray or notes. I also am using an automated account with your parameters set up as I am busy running 2 full time practices, and I figure with the filters I could watch a little less closely. However I guess I could always look at the bids every few days and a note does not look good I could pull my funding for it.

Dr. Welch, I run all three different filters on the one account and I give them order of priority based on their number from that post – so filter 1 gets first priority and so on.

As for your Lending Club question, I obviously don’t know your financial situation but I always recommend investors open an account at both companies. It gives you more diversification and some times loans are easier to come by on one platform than the other.

Your last point about checking in every few days that is not the way I do it. I let my filters run because I want a high return with the minimum amount of work. But I know many investors who like to read through every note they invest in. I have several thousand notes and it is just not feasible for me to do this.

I set up the 4 prosper settings that you have and have set up screen shots so you can let me know if they are correct. I am excited to have a more focused stratagyto try to get me into that 9-10% club and will be a regular on this board.

I think I got it all hammered out but will show you just incase… I am a bit OCD so things like this drive me crazy… I just want to make sure everthing is perfect so I will type in all the parameters for the 4 filters that I am running on Prosper that you provided:

I think I got it all hammered out but will show you just incase… I am a bit OCD so things like this drive me crazy… I just want to make sure everthing is perfect so I will type in all the parameters for the 4 filters that I am running on Prosper that you provided:

Prosper Filter #4
Prosper Rating: D, E, HR
Now Delinquent: 0 to 0
Delinquencies in last 7y: 0 to 0
Public records in last 10y: 0 to 0
Inquiries in last 6m: 1 to 2
Debt/income ration: 0 to 75%
open credit lines: 10 to 99
Bankcard utilization: 0 to 95%
Employment states (all checked except) Not employed and Not avalible
Total payments billed: .0 to 0

Sorry about being a pest but as I said I am OCD and not knowing that I am doing this 100% will literally drive me crazy.

Can anybody help me on my school project? I am trying to gather information about the pain points of investors in LendingClub. If you are an investor in LendingClub and can spare 10 minutes it will be very helpful to me.. This is a survey through SurveyMonkey. Thanks much for your help!

Can anybody help me on my school project? I am trying to gather information about the pain points of investors in LendingClub. If you are an investor in LendingClub and can spare 10 minutes it will be very helpful to me.. This is a survey through SurveyMonkey. Thanks much for your help!

When you download the spreadsheet of in funding loans from the Browse Notes screen at Lending Club one of the fields has the URL for the loan. You can just copy and paste this field into a browser and invest from there.

[…] how to setup the filtering. As an example I use my Lending Club Filter 1 that I defined in my How am I Investing in 2012 post. This video is just for Lending Club investors, when the Prosper data is available I will do […]

[…] a couple of times but it is primarily my Lending Club Filter 1 that I described early last year in this post. This past quarter saw four new defaults hit this account so my TTM return has dropped from 15.18% […]

[…] 7, 2013 TweetMy most popular post from last year in terms of both comments and page views was my How I am Investing post. I have had numerous requests from people asking if I will be updating it for this year. The […]

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